{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "                                              # 使用python绘制常见函数图像"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制一元一次函数图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8t3NM3kQyufVykr8vR4CPBV1R/WY594XNpam+Wwnwwib4RqAl7yTZ/z1Fso0wZPlUBTG7\nDqdT3kRS4t8kqc9Yp1MgmcRYGjE8QvJ/r7E4SvJawIjktcTdJC/2PkrAEUNJkiRJkiRJkiRJkiRJ\nkiRJkiRJBfw/Eoebt+QJ2g8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff35402a828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#-*- coding:utf-8 -*-\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline  \n",
    "x = np.arange(0, 10, 0.1)\n",
    " \n",
    "y = x * 2 \n",
    "\n",
    "plt.plot(x, y)\n",
    " \n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制一元二次函数图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kj2Aw6DqEQpUubVXu6NG2AcWMGXD66TYpqkoV2zykVy/rnF2zxnYfipdQyJbX\nnTkTHn0U7rorSIUKNjs3LQ1efhl27oS337bmJSX24vHD+zNZlYzy650NbMhzfyPQMMrnEB9LSzu0\nrO2gQbZZyPLl1twxbZptILJjB5x/vjXl1K0LtWpB5co2S7Zy5eI3heTkWFv5li324bF69aFLZqY9\npmFDaNAAmjSxjuHy5aP/bxeJp2gnd7W3SLGccIIl1QYNbJkDgJ9/tqS7apVdpk61xLx5s12feCKc\ncQacdJJdTjwRjgt/Bw2FrBnol1/g119hzx5L7GXL2hr2551nHxZXXmmdobVr2y5HuX0A6elK7JIc\not3m3ghIxzpVAQYCORzeqboGqBnl84qIJLu1wHmuTl4yHEA14ARgOVDHVTAiIhI9LbERM2uwyl1E\nRERERPzkVmAVcBDIvyr4QGA1kAk0j3NcySAdG5n0VfjS4piPloK0wN5/q4FHHceSDNYD32Dvx8Vu\nQ/GlccA2YEWeY+WB+cD3wDwgYWaIXADUBhZyeHKvi7XNH4+11a9Bq1UW12Cgn+sgfKwE9r6rhr0P\n1VcUuXVYMhJvmgCXc3hyHwo8Er79KDDkWC8QzySaiX3i5NcGmIJNelqP/SdrEL+wkoaPJvQnHE2+\niw29J71bBPyY71hrYGL49kSg7bFeIBEq5LOwJoVcG7HJUFI8DwJfA6+TQF/XfKKgyXd6D0YmBCwA\nlgL3OI4lWVTEmmoIX1c81oOjPYlpPlDQtgSPAbOL8TqaDHWko/1uHwdeAf4Svv8U8CLQLU5xJQO9\n36LvamALcAb23s3EqlGJjhCFvG+jndxv8PCcTUDeBWGrhI/J4Yr6ux1L8T5I5cj3YFUO/zYpxbcl\nfL0DeBtr+lJyj8w2rMDbClQGth/rwa6aZfK2xb0H3I5NeqoO1EK968VVOc/tWzi8E0YKtxR731XD\n3oe3Ye9L8eZEIHeJtZOwEXB6T0buPaBL+HYX4B2HsRzmFqxdcx/2yTMnz88ewzq0MoEb4x+a772B\nDTv7GvuDH7MtTgqkyXfRUx0bcbQcWIl+n15MATYDB7C82RUbfbSABBwKKSIiIiIiIiIiIiIiIiIi\nIiIiIiIiIiIiIiIp6P8BPMMrBpC86C4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff339566be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline \n",
    "x = np.arange(-10, 10, 0.1) \n",
    "\n",
    "y = x**2 + 2*x + 1\n",
    "\n",
    "plt.plot(x, y)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制指数函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff338e49f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import math\n",
    "%matplotlib inline \n",
    "x = np.arange(0, 10, 0.1)\n",
    " \n",
    "y = 2**x\n",
    " \n",
    "plt.plot(x, y)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 自然对数函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff338d19908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import math\n",
    "%matplotlib inline \n",
    "x = np.arange(0, 10, 0.1)\n",
    " \n",
    "e = math.e\n",
    " \n",
    "y = e**x\n",
    " \n",
    "plt.plot(x, y)\n",
    "plt.show()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制正弦函数图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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acY0vIkVUWA82Gzgrn88/BUwJ4/trdtWjTjjBVuR07mwrckaNgkcftTPuzz0X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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff338e7c390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline \n",
    "# linspace 第一个参数序列起始值, 第二个参数序列结束值,第三个参数为样本数默认50\n",
    "x = np.linspace(-np.pi, np.pi, 100)\n",
    " \n",
    "y = np.sin(x)\n",
    " \n",
    "plt.plot(x, y)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
